The inspection of building structures, especially bridges, is currently made by visual inspection. The few non-visual methodologies make use of wired sensor networks, which are relatively expensive, vulnerable to damage, and time consuming to install. Systems based on wireless sensor networks should be both cost efficient and easy to install, scalable and adaptive to different type of structures. Acoustic emission techniques are an additional monitoring method to investigate the status of a bridge or some of its components. It has the potential to detect defects in terms of cracks propagating during the routine use of structures. However, acoustic emissions recording and analysis techniques need powerful algorithms to handle and reduce the immense amount of data generated. These algorithms are developed on the basis of neural network techniques and - regarding localization of defects - by array techniques. Sensors with low price are essential for such monitoring systems to be accepted. Although the development costs of such a system are relatively high, the target price for the entire monitoring system will be several thousands Euro, depending on the size of the structure and the number of sensors necessary to cover the most important parts of the structure. Micro-Electro-Mechanical-Systems and hybrid sensors form the heart of Motes (network nodes). The network combined multi-hop data transmission techniques with efficient data pre-processing in the nodes. Using this technique, monitoring of large structures in civil engineering becomes very efficient including the sensing of temperature, moisture, strain and other data continuously. In this paper, the basic principles of a wireless monitoring system equipped with MEMS sensors is presented along with a first prototype. The authors work on details of network configuration, power consumption, data acquisition and data aggregation, signal analysis and data reduction is presented.